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big data analytics

How to Improve Employee Management using Big Data?

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Analytics and reports with big data are the new assets into HR management and business. As data is the new fuel, businesses have adopted it as very important tool for improved customer experience, sales, productivity, and similar areas. Improving employee management and employee experience are some more and important applications of big data and analytics. In today’s date, a huge number of companies can be seen investing in tools like HR management software for big data. The dedicated HR software can help in tracking and storing helpful data. Later, this data can therefore be evaluated and improvisation in strategies can be brought. Tailored HR software with an integrated employee management system can provide crucial data like performance, KPI, and so on. HR and employee management can be...

Data Warehouses vs. Data Lakes

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All data-driven organizations use data in three ways: To report on the past To understand the present To predict the future Data warehouses and Business Intelligence (BI) tools support reporting and analytics on historical data while data lakes support newer use cases that leverage data for machine learning, predictions, and real-time analysis. At Qubole, we have worked with more than 300 market-leading companies to address their data platform needs and based on our experience, we can net the differences between the two technologies to the following points: Support for the diversity of use cases Support for the diversity of data types Open vs proprietary architecture Support For The Diversity Of Use Cases Data warehouses are purpose-built and optimized for SQL-based access to support BI bu...

Can data save lives?

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Imagine if all of your personal health data is available on a single digital platform! You could also possibly run some tools over it to figure out the best possible medical programs for you- or government could use it to gauge overall health of a nation. The idea is not too far-fetched since Indian Government recently launched a policy called National Open Digital Ecosystem (NODE). One of it’s main focus would be to accumulate citizen’s health data that is currently scattered across various platforms in the country. The initiative is expected to: issue guidelines for states, departments, ministries and private institutions to bring all of their data in a common format. instruct the different parties involved to allow interoperability between datasets stored in different organizations. des...

Decoding Data Lakes

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 Those familiar with the Business Intelligence space will know of the role of a Data Warehouse. A data warehouse accumulates data from multiple sources, with the objective of providing analytics that drive business decisions.  In today’s world of big data, we have started hearing a lot about data lakes. Data lakes, like a data warehouse, is a storage repository for vast amount of data.  So, then, is a data lake a different implementation of the data warehouse?  In fact, it is quite different. The term data lakes was coined by James Dixon, former CTO of Pentaho.  According to Dixon, data warehousing led to information silos, which could be overcome by data lakes. The data lake metaphor emerged because ‘lakes’ are a great concept to explain one of the basic principles of big data – the...

The Key to Building Data Pipelines for Machine Learning: Support for Multiple Engines

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As a consumer of goods and services, you experience the results of machine learning (ML) whenever the institutions you rely on use ML processes to run their operations. You may receive a text message from a bank requiring verification after the bank has paused a credit card transaction. Or, an online travel site may send you an email that offers personalized accommodations for your next personal or business trip. The work that happens behind the scenes to facilitate these experiences can be difficult to fully realize or appreciate. An important portion of that work is done by the data engineering teams that build the data pipelines to help train and deploy those ML models. Once focused on building pipelines to support traditional data warehouses, today’s data engineering teams now build mo...

Unlocking the Power of BIG DATA !

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 “Data is a precious thing and will last longer than the systems themselves.” –  Tim Berners-Lee, Inventor of the World Wide Web” Big Data is the need of today’s hour. The use of Big Data is becoming common these days by the companies to outperform their peers. We are currently in a data-driven economy where no organization can survive without analyzing the current and future trends. It helps the organizations to combine and analyze the industry data. There are ample of information that companies have about the products, services, buyers and suppliers, consumer preferences which can be put together to analyze. So it is rightly said by Napoleon Bonaparte, “War is 90% information.” Let’s see how much true it is. Big Data can serve to deliver benefits in various domains- Insurance – As big da...

5 Techniques to draw insights from data

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“Data is the new oil.” — Clive Humby Clive Robert Humby OBE is a British mathematician and entrepreneur in the field of data science and customer-centric business strategies. It is rightly pointed by him about data. Each & every industry/business is standing on the pillars of data. Facebook, Jio – two separate industry players yet united by Data to take on the globe. Data is driving business & making them run faster than ever.  Below are the 5 techniques used by almost all industries to draw insights from Data.  Analytics One of the widely used tools to derive actionable insights from your data, is analytics.  Let us understand what Analytics is. It is the practice of managing, capturing & deriving meaningful insights by turning raw data into information.  For example, it...

DStreams vs. DataFrames: Two Flavors of Spark Streaming

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This post is a guest publication written by Yaroslav Tkachenko, a Software Architect at Activision. Apache Spark is one of the most popular and powerful large-scale data processing frameworks. It was created as an alternative to Hadoop’s MapReduce framework for batch workloads, but now it also supports SQL, machine learning, and stream processing. Today I want to focus on Spark Streaming and show a few options available for stream processing. Stream data processing is used when dynamic data is generated continuously, and it is often found in big data use cases. In most instances data is processed in near-real time, one record at a time, and the insights derived from the data are also used to provide alerts, render dashboards, and feed machine learning models that can react quickly to new t...

From Data to Decision: The Digital Marketer’s Journey

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“We must move from numbers keeping score, to numbers that drive better actions.” –David Walmsley, Chief Customer Officer at House of Fraser What is the hype today around data, digital strategy and informed decision making? Why is everyone, including the big names in every industry, gushing towards leveraging the power of data-driven decisions to bring superior and indisputable value to their client’s tables? How can the exorbitant amount of data and information available to us, help drive business with assured returns and productivity? One thing is for sure, metrics do matter, but there is a lot of confusion on which ones. Gathering numbers just to “keep score” is a fruitless tactic today. Decoding the numbers and data through analytics into valuable insights and further extracting sense f...

Demystifying Tech for the TECHADE: Big Data & Analytics (BDA)

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With plethora of data at our disposal, big data and business analytics solutions are bound to witness an increasing enterprise-wide demand. This demand is expected to be led by strong executive-level initiatives targeted at faster, decision-contextualised, and predictive insights, which could be drawn from the available data. The data could be business data, consumer data, and machine-to-machine data, analysed on cognitive platforms, at decentralised locations, and often for real-time impact. Big data analytics can help businesses make faster data-driven decisions, improve operational efficiency and reduce costs by understanding consumer behaviour. Source: SAS Global State-of-the-Market for BDA As per IDC, the global BDA solutions revenue stood at USD 189 bn. in 2019 and is expected to rea...